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Fast Unsupervised Location Category Inference from Highly Inaccurate Mobility Data
3 references·0 citing·14 second hop
Fast Unsupervised Location Category Inference from Highly Inaccurate Mobility Data (2019)Fast Unsupervised Location Category Infer…Where Did You Go (2016)Where Did You GoAn Unsupervised Collaborative Approach to Identifying Home and Work Locations (2016)An Unsupervised Collaborative…Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs (2014)Modeling User Activity Prefer…Friendship and mobility (2011)Discovering regions of different functions in a city using human mobility and POIs (2012)Participatory Cultural Mapping Based on Collective Behavior Data in Location-Based Social Networks (2016)Revisiting User Mobility and Social Relationships in LBSNs: A Hypergraph Embedding Approach (2019)A Survey on Deep Learning for Human Mobility (2021)Exploring Millions of Footprints in Location Sharing Services (2021)Using GPS to learn significant locations and predict movement across multiple users (2003)Identifying Important Places in People’s Lives from Cellular Network Data (2011)Home Location Identification of Twitter Users (2014)Understanding individual human mobility patterns (2008)Limits of Predictability in Human Mobility (2010)A Survey on Spatial Prediction Methods (2018)DeepMove (2018)PeriodicMove (2021)
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References

  • 2014Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs879 cited
  • 2016Where Did You Go47 cited
  • 2016An Unsupervised Collaborative Approach to Identifying Home and Work Locations5 cited

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